On Sat, Jun 23, 2012 at 7:42 PM, Daniel Duckworth <[email protected]> wrote: > Hello everyone, > > I would like to ask for those willing to begin reviewing my new > sklearn.kalman module (found > here: https://github.com/scikit-learn/scikit-learn/pull/862 ). It is a > module that implements the Kalman Filter, Kalman Smoother, and EM algorithm > for Linear-Gaussian models with the ability to handle missing observations. > As far as Kalman Filter implementations go, I believe it is already more > complete than any other package I've seen for Linear-Gaussian state > estimation. As it is currently implemented in pure Python/NumPy, there is > significant room for speed improvements, but the core implementation is > correct and readily usable. I have included documentation ( > doc/modules/kalman.rst ), examples ( examples/kalman ), a dataset for > testing ( sklearn/datasets/data/kf_vars.mat ), and test cases with 90% > coverage ( sklearn/tests/test_kalman.py ). > > Any and all comments are appreciated, and I would really love to see this > module accepted into sklearn. Let me know if there's anything I can do to > make your job easier! >
A very minor point as I have a look, adding the kalman subpackage in sklearn/setup.py would be nice so that it installs. As far as I can see it doesn't right now unless I missed something. Skipper ------------------------------------------------------------------------------ Live Security Virtual Conference Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
